What if Big Brother had access to big data technology? Big data handled without care might easily turn us all unknowingly into Big Brothers or their collaborators.

Although some might see it differently, the society foreseen and described by George Orwell in the dystopian novel 1984 has not become reality. But what if Big Brother had access to big data technology? Big data handled without care might easily turn us all unknowingly into Big Brothers or their collaborators.

Big Brother is symbolic of the totalitarian state Oceania where every citizen was under constant surveillance by the authorities.

Digital computers just recently were invented when 1984 was published in 1949 and were hardly known to people in general. Computers and big data play no real role in the novel, but it is easy to imagine what Big Brother could have done if they were able to capture, curate, manage and process huge volumes of data.

Big Brother better off with computers

Without doubt, Big Brother would be far better off with big data capabilities. They had the manpower but not the necessary data tools.

Today we have those tools. We do not even need the manpower Big Brother possessed. Automatic capture and processing of tremendous amounts of data can be handled by computers, machine learning and Artificial Intelligence, assisted by a few people.

What we define as big data lakes are key and the resource for big data analyses. The data lake sources can be multiple and the potential results from data analyses can be very interesting.

Huge big data potential

By looking into big data, we can reveal customers and entire societies, including new ways of services distribution and even entire new business models. Basefarm is capable of providing these kinds of analyses.

The view of some big data evangelists is that companies possessing big data capacities might be in position to redefine their entire business. For instance, logistic companies produce enormous amounts of data. Evangelists suggest that these data represent such value that utilizing the data can be core for such companies in the future, not the original logistics business.

Will they also become Big Brothers?

Avoid the dark path

Unless companies are careful, that might very well be the outcome. The path to Big Brother status starts with what data you collect in in the big data lake.

Security and compliance are an integrated part of daily Basefarm operations. The value of this knowledge is even higher in the new world of increasing capabilities to collect, curate, communicate and move data.

Without compliance work, we can all easily step over the threshold and become something far from our intentions.

The Ministry of Love wants your logs

An example of the road to becoming Big Brother is how we handle logs. Infrastructure and application logs are true big data sources. In Basefarm we are enthusiastic about the opportunities provided by these sources. So much information is available to increase production and the customer experience, even leading to completely new ways of serving our customers.

However, logs contain geographical distribution, processing and personal data which are regulated in GDPR. Not least, a big topic is who can access the data. If the logs contain information about personal health, maybe only medical doctors or psychologists are allowed to access them. You definitely don’t want them falling into the hands of Big Brother.

The log data example is interesting. For all Basefarm knows, IT staff might already be unknowingly handling logs in a way that does not comply with regulations.

Unknowing collaborator

No sane person would like to be associated with Big Brother. We do not want to contribute to others becoming Big Brother, and definitely not by them using our data.

To avoid this we need comprehensive control of our data. We need to control where it is, what it contains, who has access and how it is shared with governments, service partners and companies which provide big data services like Basefarm.

The key to avoiding collaborating with Big Brother is to handle your data correctly. It is a priceless asset for your business and you don’t want it falling into the wrong hands.Don’t risk becoming a Big Brother. Through compliance with GDPR and other regulations we can derive huge value from big data.

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Data Thinking addresses the subject areas of our time: data, algorithms, compute and mindset. To comprehensively support companies during times of great complexity and to supervise them with their own digital development. Learn how you can benefits from Data Thinking.

The rise of big data opens up new possibilities. By investing in the future and exploring use cases together with customers in many industries, Basefarm creates market leaders.

The rise of big data opens up new possibilities. By investing in the future and exploring use cases together with customers in many industries, Basefarm creates market leaders.

Use cases for big data projects are everywhere. Take, for instance, predictive maintenance in the offshore industry (e.g. wind turbine maintenance) and the merits of the 360-degree customer view in the hospitality industry. But to flourish in this rapidly evolving world, it’s increasingly important to be agile and flexible. Many of Basefarm’s customers face the challenge of mixing and matching agile ways of working (such as DevOps environments) with traditional processes and infrastructures, resulting in a hybrid delivery model and a hybrid business.

“With this in mind, areas such as security, IoT and big data need extra focus,” says Stefan Månsby, Senior Director of Product Management & Big Data at Basefarm. “With our security division, we deliver 24/7 security services. And now we are also helping many of our customers to understand that very often, they have a golden opportunity to apply their domain expertise to their existing wealth of unexplored data.”

Data is the new oil

Businesses themselves are also becoming more data-driven. Companies are becoming more “hybrid” from a technical point of view, mixing and matching traditional and modern IT infrastructures. By making all their data available in one large pool, they embrace a new way of decision-making where companies rely on data science. Often, this opens up new possibilities for non-linear growth, leading to companies crossing the traditional boundaries between industries. A well-known example of this is Tesla. In their mission is to accelerate the world’s transition to sustainable energy, they build solar panels, batteries and electric cars.

A comparison to Tesla doesn’t do much justice to most companies. But this doesn’t mean they shouldn’t embrace big data. The most typical big data use cases show up in manufacturing, service and maintenance. The potential benefits of predictive maintenance, for example, are huge. By collecting and analyzing data from machine parts, it becomes possible to predict failure and to schedule maintenance. One Basefarm customer performs maintenance on wind farms in the Baltic Sea. With only a few ships available that can hoist ball bearings into wind turbines, they save millions of euros every year by letting AI calculate the optimal shipping routes.

You have the data; now use it

There are numerous examples of big data use cases. Månsby: “At Basefarm, we organize workshops with our customers which generate hundreds of ideas and scenarios.”

The next step is often to design a Proof of Concept (PoC) to present to the company’s board.

“Basically, we can go from whiteboard to a working first PoC in 8 to 12 weeks,” Månsby says. “The size of the company doesn’t matter. Whether you are BMW or a small enterprise, it doesn’t make any difference. If your company has a top-heavy culture, for instance, and data science seems a bit too ‘Star Trekky’ for the CXO’s, we sometimes give the CXO access to a small subset of data to play around with on a Notebook. So they get a feel for the possibilities and start to understand that this technology isn’t black magic or an experimental lab product. It’s very real, it’s now and helps you achieve big goals like major improvements in efficiency, becoming more sustainable and finding new revenue streams.”

About Stefan Månsby

Stefan Månsby is Senior Director of Product Management & Big Data at Basefarm. He has a broad experience in the IT industry and has driven change in many organizations throughout the years. His main passion is digital innovation and he is a great photographer and music producer.

https://blog.basefarm.com/wp-content/uploads/2018/03/Data-thinking.jpeg16672500Stefan Månsbyhttps://blog.basefarm.com/wp-content/uploads/2018/03/basefarm-logo-blue-1.pngStefan Månsby2018-02-25 15:40:522018-03-16 16:07:48Data is stupid; using it is clever

Apple fixes that “1 character to crash your Mac and iPhone” bug

Apple has pushed out an emergency update for all its operating systems and devices, including TVs, watches, tablets, phones and Macs.

The fix patches a widely-publicised vulnerability known officially as CVE-2018-4124, and unofficially as “one character to crash your iPhone”, or “the Telugu bug”.

Telugu is a widely-spoken Indian language with a writing style that is good news for humans, but surprisingly tricky for computers.

Computers can store and reproduce English words really easily, because there are only 26 symbols (if you ignore lower-case letters, the hyphen and that annoying little dingleberry thing called the apostrophe that our written language could so easily do without).

Many languages use a written form in which each character is made up of a combination of components that denote how to pronounce it, typically starting with a basic sound and indicating the various modifications that should be applied to it.

In English, each left-arrow or right-arrow simply moves you one character along in the current line, and one byte along in the current ASCII string, but what if there are four different sub-characters stored in memory to represent the next character that’s displayed?

For your iPhone, you ‘ll be updating to iOS 11.2.6; for your Mac, you need the macOS High Sierra 10.13.3 Supplemental Update.

Where does success come from? Nowadays, data thinking is a key component. It’s the culture that is responsible for SpaceX’s pioneering Falcon Heavy rocket launch as well as the secret behind hotels and bars remembering your favorite drink.

If there is anything that drives the most successful businesses right now, it is the clever use of data. Seen in this light, the acquisition by Basefarm of the Berlin-based The Unbelievable Machine Company (*um), the leading service provider for big data, cloud and managed cloud services in Germany and Austria, comes at exactly the right moment.

“Many of our customers are huge data owners. Data is the asset of the future,” explains Stefan Månsby, Senior Director of Product Management & Big Data at Basefarm. “European companies need to catch up with their North American counterparts. The big boys in Silicon Valley, such as Amazon and Google, are leading the race and there is nothing wrong with that. But some parts of Europe lag almost a decade behind when it comes to big data maturity. This needs to change.”

Great data leads to great ideas

Amongst many other industries, airlines and leisure companies will benefit greatly from having a 360-degree view of the customer. By gaining insight into customer behavior and needs, they can turn the customer’s next flight or stay into a ”super-tailored experience” because they already know the customer’s exact preferences. Even a result as simple as having your favorite drink waiting for you when you arrive at a hotel can make a big difference. But how do you get there as a company? You have to concentrate on data first, by putting all your data in one place.

“The first thing we recommend is what we call ‘data thinking’,” says Månsby. ” You provide the essential hard data so a company can make necessary decisions “Part of this is data science. You test hypotheses and either they make sense and get you the revenue, or they are a bad idea but you learn from it. By investing in such an agile culture, you can set yourself apart from your competitors and gain a market advantage. Focus on the idea of what you would like to do, not how you will technically solve it. The idea will make your business unique and a leader, not the technology.”

Elon Musk: solar panels, batteries, cars and rockets

A big difference between traditional business and business that relies on data thinking lies in the way they evolve. With the latter, this is far from linear. An example is a company that builds self-driving buses. Their core business is to make such vehicles but, once the buses are driving around in cities, the company can start a side business in traffic reports based on the data they have collected. The new revenue streams could potentially even make public transport free for passengers.

“Data thinking enables new opportunities,” Månsby says. “Look at Ikea. Data thinking has made it Sweden’s second largest food exporter. Another example is Tesla, their mission is to accelerate the world’s transition to sustainable energy. Hence, they need to develop the ultimate battery and then apply them in great cars to prove their point. That’s amazing. As a data-thinking company, you have a big advantage over linear competitors.”

About the Author

Stefan Månsby is Senior Director of Product Management & Big Data at Basefarm. He has a broad experience in the IT industry and has driven change in many organizations throughout the years. His main passion is digital innovation and he is a great photographer and music producer.

Think data lakes are just a new incarnation of data warehouses? Our resident expert Ingo Steins rates the two.

Data lakes and data warehouses only have one thing in common, and that is the fact that they are both designed to store data. Apart from that, the systems have fundamentally different applications and offer different options to users.

A data warehouse is a central repository for company management, so it’s quite different. Its primary role is as a component of business intelligence: it stores figures for use in process optimization planning, or for determining the strategic direction of the company. It also supports business reporting, so the data it contains must all be structured and in the same format.

Challenges with data warehouses

Data warehouses aren’t actually designed for large-scale data analysis, and when used in this way these systems will reach their structural and capacity limits very quickly. We now generate enormous volumes of unstructured data which needs to be processed quickly.

Another limitation is the fact that high-quality analyses now draw on a variety of different data sources in different formats, including social media, weblogs, sensors and mobile technology.

Data warehouses also suffer from performance weaknesses. Their loading processes are complex and take hours, the implementation of changes is a slow and laborious process, and there are several steps to go through before you can generate even a simple analysis or report.

Virtually limitless data lakes

Data lakes, on the other hand, are virtually limitless. They aren’t products in the same way that data warehouses are, but are more of a concept that is put together individually and can be expanded infinitely.

Data lakes can store infinite different data formats in very high volumes for indefinite periods of time. Because they are built using standard software, the memory is comparatively cost-effective too.

Data lakes can store huge volumes of data, but need no complex formatting or maintenance. The system doesn’t impose any limits on processes or processing speeds – in fact, it actually opens up new ways to exploit the data you have, and can therefore help companies more generally in the process of digitalization.

Put on your swim suit

All you really need to start a data lake is a suitable database. This is relatively easy to set up with a solution like Hadoop. Companies who want to access a wide range of data and process it effectively in real time to answer highly specialized and complex questions will find that the data lake is the perfect infrastructure to realize this goal.

Ingo Steins

Ingo Steins is Unbelievable Machine’s Deputy Director of Operations, heading up the applications division from our base in Berlin. He has years of experience in software, data development and managing large teams, and now runs three such teams distributed across our sites. Ingo joined The Unbelievable Machine Company in January 2016.

Beginning in July 2018 with the release of Chrome 68, Chrome will mark all HTTP sites as “not secure”.

For the past several years, we’ve moved toward a more secure web by strongly advocating that sites adopt HTTPS encryption. And within the last year, we’ve also helped users understand that HTTP sites are not secure by graduallymarking a larger subset of HTTP pages as “not secure”.

Over 68% of Chrome traffic on both Android and Windows is now protected